To mark International Girls in ICT Day on 23 April, Michelle Li, Palladium Technical Advisor on USAID’s Data for Implementation project (Data.FI), shares three ways that data can be used to strengthen HIV programs for girls and women.
While COVID-19 is the most urgent health priority across the globe, HIV remains an ongoing crisis — and one to which women and girls in many countries are particularly vulnerable due to discrimination, inability to negotiate safe sex, and curtailed access to HIV services.
In this digital age, we are generating unprecedented volumes of data and benefitting from increasingly sophisticated analytics to glean novel information. HIV programs now have a wealth of health data available to target gender-equitable HIV and violence prevention interventions, from traditional sources (such as electronic medical records or laboratories) to data generated by mobile phones, wearable health technologies, electronic sensors, and social media.
USAID’s Data for Implementation project (Data.FI) is working to improve the quality, availability, and use of data to strengthen and scale HIV services, applying three principles to ensure that girls and women are not left behind in the data revolution:
Make Use of Existing Data
We need to be intentional about how we use existing data on girls and women to design better policies and programs. This is particularly important for HIV programs, as an estimated 74% of new infections in Africa occur among adolescent girls aged 15-19 years.
In Uganda, Data.FI analysed survey data from the Uganda Population-based HIV Impact Assessment to understand risk factors for HIV infection and derived population estimates for adolescent girls and young women. This gender-specific analysis was used to support decisions for expanding the DREAMS (Determined, Resilient, Empowered, AIDS-free, Mentored and Safe) program that delivers a core package of evidence-based interventions to address the multiple and interlocking challenges faced by this vulnerable group.
Recognise Blind Spots and Biases in Data
We must acknowledge that there are implicit gender biases in many sources of data, promote transparency in datasets, and design analyses to account for these biases. For example, in many developing countries, girls are less likely to own a mobile device and have less access to the Internet compared with boys and men. Mining social media data or search terms to understand emerging HIV-related behaviours could be useful for predicting HIV hotspots, but this analysis might leave out important trends among women and girls.
Analysing transportation data to understand population mobility could be a useful way to identify the optimal location of essential HIV services, including testing and antiretroviral therapy distribution points. However, analysis of data from transportation apps, call records, or roadway networks is unlikely to yield results that speak to the gendered dimensions of mobility, labour patterns, and transportation preferences. Recommendations informed from these data may not reflect the experiences lived by women and could result in less effective programs.
Empower Women as Data Users and Producers
We need to put data in the hands of girls and women. When women are empowered to advocate for improved data collection and trained to design technology-enabled analyses, they can better identify gender biases in data and lead efforts to ensure that analyses are representative of women. This means that more accurate and relevant conclusions can be drawn from data to better inform program decisions that affect the health of women and girls.
In Nigeria, Data.FI is incorporating sex-disaggregated indicators into data visualizations and dashboards and promoting gender-balanced participation in weekly data review meetings. During these facilitated reviews, we encourage decision makers to interpret data and refine program approaches based on gender differences observed.
A common analogy states that “data is the new oil” — it brings value to those who can effectively extract meaningful insights from raw inputs. Applying these principles can help girls and women gain the necessary skills and tools to use data that are relevant to their needs, advocate for interventions that improve gender-equitable HIV services, and lead the data revolution.
Data.FI is funded by USAID under PEPFAR and implemented by Palladium. Contact email@example.com to learn more.